In [23]:
t = bat[['batsman','Hundreds',"Fifties"]].iloc[:upto].sort_values(['Fifties','Hundreds'])
pas = t.melt(id_vars='batsman',value_vars=['Fifties','Hundreds'])
pas = pas.pivot(columns='batsman',index='variable',values='value')
dict = pas.to_dict()
keys = dict.keys()
top_list=[]
for i in keys:
top_list.append(i)
for i,j in enumerate(top_list):
plot_list=[]
plot_list.append(dict[top_list[i]]['Fifties'])
plot_list.append(dict[top_list[i]]['Hundreds'])
dict[top_list[i]]=plot_list
category_names = ['Fifties','Hundreds']
results = dict
def survey(results, category_names):
"""
Parameters
----------
results : dict
A mapping from question labels to a list of answers per category.
It is assumed all lists contain the same number of entries and that
it matches the length of *category_names*.
category_names : list of str
The category labels.
"""
keys = results.keys()
labels = []
for i in keys:
labels.append(i)
data = np.array(list(results.values()))
data_cum = data.cumsum(axis=1)
category_colors = plt.get_cmap('RdYlGn')(
np.linspace(0.15, 0.85, data.shape[1]))
fig, ax = plt.subplots(figsize=(14, 8))
ax.invert_yaxis()
ax.xaxis.set_visible(False)
ax.set_xlim(0, np.sum(data, axis=1).max())
for i, (colname, color) in enumerate(zip(category_names, category_colors)):
widths = data[:, i]
starts = data_cum[:, i] - widths
rects = ax.barh(labels, widths, left=starts, height=0.5,
label=colname, color=color)
r, g, b, _ = color
text_color = 'white' if r * g * b < 0.5 else 'darkgrey'
# ax.bar_label(rects, label_type='center', color=text_color)
ax.legend(ncol=len(category_names), bbox_to_anchor=(0, 1),
loc='lower left', fontsize='small')
ax.set_title(f'''Fifties vs Hundreds for top {upto} run scorers''')
return fig
figure = survey(results, category_names)
